Overview

Dataset statistics

Number of variables8
Number of observations11469
Missing cells31928
Missing cells (%)34.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory716.9 KiB
Average record size in memory64.0 B

Variable types

Text1
Numeric7

Alerts

lbl 0 is highly overall correlated with lbl 1 and 4 other fieldsHigh correlation
lbl 1 is highly overall correlated with lbl 0 and 4 other fieldsHigh correlation
lbl 2 is highly overall correlated with lbl 0 and 4 other fieldsHigh correlation
lbl 255 is highly overall correlated with lbl 0 and 4 other fieldsHigh correlation
lbl 3 is highly overall correlated with lbl 0 and 4 other fieldsHigh correlation
mean_positive is highly overall correlated with lbl 0 and 4 other fieldsHigh correlation
lbl 0 has 6335 (55.2%) missing valuesMissing
lbl 1 has 6696 (58.4%) missing valuesMissing
lbl 2 has 8368 (73.0%) missing valuesMissing
lbl 3 has 10529 (91.8%) missing valuesMissing
labeler has unique valuesUnique

Reproduction

Analysis started2024-07-25 15:55:58.089491
Analysis finished2024-07-25 15:56:12.545106
Duration14.46 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

labeler
Text

UNIQUE 

Distinct11469
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:12.871628image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length20
Median length20
Mean length13.662046
Min length2

Characters and Unicode

Total characters156690
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11469 ?
Unique (%)100.0%

Sample

1st row1966806
2nd row1981715
3rd row2121542
4th row2125241
5th row2126641
ValueCountFrequency (%)
1966806 1
 
< 0.1%
2125034 1
 
< 0.1%
2093369 1
 
< 0.1%
2127850 1
 
< 0.1%
2121542 1
 
< 0.1%
2125241 1
 
< 0.1%
2126641 1
 
< 0.1%
2129143 1
 
< 0.1%
1567354 1
 
< 0.1%
2125227 1
 
< 0.1%
Other values (11459) 11459
99.9%
2024-07-25T17:56:13.552547image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15645
 
10.0%
1 14255
 
9.1%
0 11502
 
7.3%
9 10677
 
6.8%
5 10283
 
6.6%
4 10199
 
6.5%
6 10160
 
6.5%
3 9965
 
6.4%
8 9903
 
6.3%
7 9859
 
6.3%
Other values (6) 44242
28.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 156690
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 15645
 
10.0%
1 14255
 
9.1%
0 11502
 
7.3%
9 10677
 
6.8%
5 10283
 
6.6%
4 10199
 
6.5%
6 10160
 
6.5%
3 9965
 
6.4%
8 9903
 
6.3%
7 9859
 
6.3%
Other values (6) 44242
28.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 156690
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 15645
 
10.0%
1 14255
 
9.1%
0 11502
 
7.3%
9 10677
 
6.8%
5 10283
 
6.6%
4 10199
 
6.5%
6 10160
 
6.5%
3 9965
 
6.4%
8 9903
 
6.3%
7 9859
 
6.3%
Other values (6) 44242
28.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 156690
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 15645
 
10.0%
1 14255
 
9.1%
0 11502
 
7.3%
9 10677
 
6.8%
5 10283
 
6.6%
4 10199
 
6.5%
6 10160
 
6.5%
3 9965
 
6.4%
8 9903
 
6.3%
7 9859
 
6.3%
Other values (6) 44242
28.2%

weight
Real number (ℝ)

Distinct11436
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27064976
Minimum0
Maximum0.98272705
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:13.781518image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.052208061
Q10.14100552
median0.22066556
Q30.35882586
95-th percentile0.66042976
Maximum0.98272705
Range0.98272705
Interquartile range (IQR)0.21782034

Descriptive statistics

Standard deviation0.18439379
Coefficient of variation (CV)0.6813004
Kurtosis1.0515508
Mean0.27064976
Median Absolute Deviation (MAD)0.096937236
Skewness1.170982
Sum3104.0821
Variance0.03400107
MonotonicityNot monotonic
2024-07-25T17:56:13.973498image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4875936508 7
 
0.1%
0.6595439911 6
 
0.1%
0.07110118866 2
 
< 0.1%
0.1464805603 2
 
< 0.1%
0.2245769501 2
 
< 0.1%
0.1976385117 2
 
< 0.1%
0.2378552755 2
 
< 0.1%
0.1548144023 2
 
< 0.1%
0.1558771133 2
 
< 0.1%
0.5826292038 2
 
< 0.1%
Other values (11426) 11440
99.7%
ValueCountFrequency (%)
0 2
< 0.1%
0.0002374649048 1
< 0.1%
0.0003414154053 1
< 0.1%
0.001533508301 1
< 0.1%
0.001774787903 1
< 0.1%
0.001867294312 1
< 0.1%
0.002016067505 1
< 0.1%
0.002073764801 1
< 0.1%
0.002167701721 1
< 0.1%
0.002214431763 1
< 0.1%
ValueCountFrequency (%)
0.9827270508 1
< 0.1%
0.9804906845 1
< 0.1%
0.9779758453 1
< 0.1%
0.973238945 1
< 0.1%
0.9723062515 1
< 0.1%
0.9708442688 1
< 0.1%
0.9664812088 1
< 0.1%
0.9509143829 1
< 0.1%
0.9438095093 1
< 0.1%
0.9437255859 1
< 0.1%

lbl 0
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct5133
Distinct (%)> 99.9%
Missing6335
Missing (%)55.2%
Infinite0
Infinite (%)0.0%
Mean0.22306476
Minimum2.4604241 × 10-6
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:14.157478image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum2.4604241 × 10-6
5-th percentile0.0054284555
Q10.036630466
median0.11085543
Q30.30221701
95-th percentile0.93045158
Maximum1
Range0.99999754
Interquartile range (IQR)0.26558654

Descriptive statistics

Standard deviation0.26967237
Coefficient of variation (CV)1.2089421
Kurtosis1.6800385
Mean0.22306476
Median Absolute Deviation (MAD)0.089291644
Skewness1.6328368
Sum1145.2145
Variance0.072723186
MonotonicityNot monotonic
2024-07-25T17:56:14.384447image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2
 
< 0.1%
0.1038858464 1
 
< 0.1%
0.1540435708 1
 
< 0.1%
0.9334711523 1
 
< 0.1%
0.1063041053 1
 
< 0.1%
0.9854109576 1
 
< 0.1%
0.9657831348 1
 
< 0.1%
0.2490471925 1
 
< 0.1%
0.08165985648 1
 
< 0.1%
0.2458244114 1
 
< 0.1%
Other values (5123) 5123
44.7%
(Missing) 6335
55.2%
ValueCountFrequency (%)
2.460424079 × 10-61
< 0.1%
2.614136169 × 10-61
< 0.1%
2.661335581 × 10-61
< 0.1%
2.855168712 × 10-61
< 0.1%
2.870931531 × 10-61
< 0.1%
3.122334277 × 10-61
< 0.1%
4.003282692 × 10-61
< 0.1%
4.681417814 × 10-61
< 0.1%
8.471029925 × 10-61
< 0.1%
9.886612189 × 10-61
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9993377153 1
< 0.1%
0.9985423545 1
< 0.1%
0.9982283681 1
< 0.1%
0.9982197513 1
< 0.1%
0.9980775741 1
< 0.1%
0.997826555 1
< 0.1%
0.9977880445 1
< 0.1%
0.9976615917 1
< 0.1%
0.9976273166 1
< 0.1%

lbl 1
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4773
Distinct (%)100.0%
Missing6696
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean0.26396027
Minimum7.3457844 × 10-7
Maximum0.9990959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:14.564429image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum7.3457844 × 10-7
5-th percentile0.0053261895
Q10.05187259
median0.15281512
Q30.3895261
95-th percentile0.90607689
Maximum0.9990959
Range0.99909516
Interquartile range (IQR)0.33765351

Descriptive statistics

Standard deviation0.27897604
Coefficient of variation (CV)1.0568865
Kurtosis0.43951078
Mean0.26396027
Median Absolute Deviation (MAD)0.12384939
Skewness1.2532667
Sum1259.8823
Variance0.077827631
MonotonicityNot monotonic
2024-07-25T17:56:14.757437image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4627779068 1
 
< 0.1%
0.05081323776 1
 
< 0.1%
0.04996269072 1
 
< 0.1%
0.08308873424 1
 
< 0.1%
0.06641827143 1
 
< 0.1%
0.1771953597 1
 
< 0.1%
0.3318679627 1
 
< 0.1%
0.02369521861 1
 
< 0.1%
0.4349657487 1
 
< 0.1%
0.3014093306 1
 
< 0.1%
Other values (4763) 4763
41.5%
(Missing) 6696
58.4%
ValueCountFrequency (%)
7.345784438 × 10-71
< 0.1%
3.912802224 × 10-61
< 0.1%
4.106959981 × 10-61
< 0.1%
6.151149112 × 10-61
< 0.1%
7.291896772 × 10-61
< 0.1%
7.988028608 × 10-61
< 0.1%
8.510245119 × 10-61
< 0.1%
1.071903271 × 10-51
< 0.1%
1.121994457 × 10-51
< 0.1%
1.31127181 × 10-51
< 0.1%
ValueCountFrequency (%)
0.9990958958 1
< 0.1%
0.9984424068 1
< 0.1%
0.9979706134 1
< 0.1%
0.9968341236 1
< 0.1%
0.99648692 1
< 0.1%
0.9961155254 1
< 0.1%
0.9958370108 1
< 0.1%
0.9954231971 1
< 0.1%
0.9953748505 1
< 0.1%
0.9941470126 1
< 0.1%

lbl 2
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3101
Distinct (%)100.0%
Missing8368
Missing (%)73.0%
Infinite0
Infinite (%)0.0%
Mean0.26820662
Minimum6.8443084 × 10-7
Maximum0.99677448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:14.940384image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum6.8443084 × 10-7
5-th percentile0.0030538595
Q10.042671579
median0.15521915
Q30.4116257
95-th percentile0.90214337
Maximum0.99677448
Range0.99677379
Interquartile range (IQR)0.36895412

Descriptive statistics

Standard deviation0.2860016
Coefficient of variation (CV)1.066348
Kurtosis0.13323658
Mean0.26820662
Median Absolute Deviation (MAD)0.13576235
Skewness1.1516609
Sum831.70874
Variance0.081796912
MonotonicityNot monotonic
2024-07-25T17:56:15.307340image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02745845133 1
 
< 0.1%
0.3099784873 1
 
< 0.1%
0.05750562435 1
 
< 0.1%
0.04916835586 1
 
< 0.1%
0.08350877825 1
 
< 0.1%
0.02003254339 1
 
< 0.1%
0.3296195329 1
 
< 0.1%
0.9696589841 1
 
< 0.1%
0.9617204829 1
 
< 0.1%
0.02743645878 1
 
< 0.1%
Other values (3091) 3091
 
27.0%
(Missing) 8368
73.0%
ValueCountFrequency (%)
6.84430841 × 10-71
< 0.1%
8.002663286 × 10-71
< 0.1%
1.785471481 × 10-61
< 0.1%
3.794533595 × 10-61
< 0.1%
6.159863585 × 10-61
< 0.1%
6.661936692 × 10-61
< 0.1%
6.742452921 × 10-61
< 0.1%
6.893017453 × 10-61
< 0.1%
1.342101731 × 10-51
< 0.1%
1.455046886 × 10-51
< 0.1%
ValueCountFrequency (%)
0.9967744758 1
< 0.1%
0.9963033491 1
< 0.1%
0.9950396945 1
< 0.1%
0.993967848 1
< 0.1%
0.992523291 1
< 0.1%
0.9925074001 1
< 0.1%
0.9917454402 1
< 0.1%
0.9915647421 1
< 0.1%
0.9913392054 1
< 0.1%
0.9907661938 1
< 0.1%

lbl 3
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct940
Distinct (%)100.0%
Missing10529
Missing (%)91.8%
Infinite0
Infinite (%)0.0%
Mean0.20290622
Minimum3.9037412 × 10-7
Maximum0.98824846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:15.511317image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum3.9037412 × 10-7
5-th percentile0.0011209141
Q10.023434786
median0.098804232
Q30.29322663
95-th percentile0.79444784
Maximum0.98824846
Range0.98824807
Interquartile range (IQR)0.26979184

Descriptive statistics

Standard deviation0.24979069
Coefficient of variation (CV)1.2310647
Kurtosis1.2011863
Mean0.20290622
Median Absolute Deviation (MAD)0.089072785
Skewness1.4977901
Sum190.73185
Variance0.062395388
MonotonicityNot monotonic
2024-07-25T17:56:15.735091image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02395461507 1
 
< 0.1%
0.2323442113 1
 
< 0.1%
0.18328125 1
 
< 0.1%
0.001723730423 1
 
< 0.1%
0.0002153425951 1
 
< 0.1%
0.008956053185 1
 
< 0.1%
0.0519701121 1
 
< 0.1%
0.02894295617 1
 
< 0.1%
0.002057014254 1
 
< 0.1%
0.05664848671 1
 
< 0.1%
Other values (930) 930
 
8.1%
(Missing) 10529
91.8%
ValueCountFrequency (%)
3.90374116 × 10-71
< 0.1%
5.374225216 × 10-61
< 0.1%
1.15442157 × 10-51
< 0.1%
1.362908447 × 10-51
< 0.1%
4.492611526 × 10-51
< 0.1%
8.430512554 × 10-51
< 0.1%
0.0001168883249 1
< 0.1%
0.0001192139786 1
< 0.1%
0.0001198771259 1
< 0.1%
0.000131906485 1
< 0.1%
ValueCountFrequency (%)
0.9882484611 1
< 0.1%
0.9719063274 1
< 0.1%
0.9571005563 1
< 0.1%
0.9517329364 1
< 0.1%
0.9497230201 1
< 0.1%
0.9417067308 1
< 0.1%
0.9404997643 1
< 0.1%
0.9400138144 1
< 0.1%
0.9283136483 1
< 0.1%
0.9263852842 1
< 0.1%

lbl 255
Real number (ℝ)

HIGH CORRELATION 

Distinct11468
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.28122979
Minimum6.2039933 × 10-5
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:15.944067image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum6.2039933 × 10-5
5-th percentile0.012394126
Q10.062079464
median0.17038347
Q30.43144975
95-th percentile0.90578032
Maximum1
Range0.99993796
Interquartile range (IQR)0.36937029

Descriptive statistics

Standard deviation0.28021159
Coefficient of variation (CV)0.99637945
Kurtosis0.11782732
Mean0.28122979
Median Absolute Deviation (MAD)0.1336097
Skewness1.1274555
Sum3225.4245
Variance0.078518533
MonotonicityNot monotonic
2024-07-25T17:56:16.136044image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2
 
< 0.1%
0.005754354148 1
 
< 0.1%
0.1233845427 1
 
< 0.1%
0.07851960977 1
 
< 0.1%
0.113624242 1
 
< 0.1%
0.463283057 1
 
< 0.1%
0.03732980998 1
 
< 0.1%
0.1140071781 1
 
< 0.1%
0.4846975994 1
 
< 0.1%
0.1522432916 1
 
< 0.1%
Other values (11458) 11458
99.9%
ValueCountFrequency (%)
6.203993251 × 10-51
< 0.1%
0.0001064591887 1
< 0.1%
0.0002505718572 1
< 0.1%
0.0002789524425 1
< 0.1%
0.0003233328563 1
< 0.1%
0.0003891546831 1
< 0.1%
0.0004174133154 1
< 0.1%
0.0004922886471 1
< 0.1%
0.0005454156725 1
< 0.1%
0.0006912171223 1
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9998809483 1
< 0.1%
0.9998280311 1
< 0.1%
0.9987758929 1
< 0.1%
0.9987179177 1
< 0.1%
0.9985884085 1
< 0.1%
0.9985180938 1
< 0.1%
0.9984898431 1
< 0.1%
0.9984606023 1
< 0.1%
0.9982138774 1
< 0.1%

mean_positive
Real number (ℝ)

HIGH CORRELATION 

Distinct11468
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26838024
Minimum6.2039933 × 10-5
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.7 KiB
2024-07-25T17:56:16.324021image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum6.2039933 × 10-5
5-th percentile0.012693657
Q10.061564665
median0.16586595
Q30.40066635
95-th percentile0.87925277
Maximum1
Range0.99993796
Interquartile range (IQR)0.33910169

Descriptive statistics

Standard deviation0.26770757
Coefficient of variation (CV)0.99749357
Kurtosis0.41273577
Mean0.26838024
Median Absolute Deviation (MAD)0.12859961
Skewness1.2023435
Sum3078.053
Variance0.07166734
MonotonicityNot monotonic
2024-07-25T17:56:16.525999image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2
 
< 0.1%
0.005612817666 1
 
< 0.1%
0.1137073433 1
 
< 0.1%
0.08710635302 1
 
< 0.1%
0.1174463481 1
 
< 0.1%
0.473304337 1
 
< 0.1%
0.03694045078 1
 
< 0.1%
0.1441330687 1
 
< 0.1%
0.4910773282 1
 
< 0.1%
0.171078428 1
 
< 0.1%
Other values (11458) 11458
99.9%
ValueCountFrequency (%)
6.203993251 × 10-51
< 0.1%
0.0001065538045 1
< 0.1%
0.0002197709656 1
< 0.1%
0.0003233328563 1
< 0.1%
0.0003420645885 1
< 0.1%
0.0003806457589 1
< 0.1%
0.0004846053401 1
< 0.1%
0.0004922886471 1
< 0.1%
0.0005338939435 1
< 0.1%
0.0005796589139 1
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9987758929 1
< 0.1%
0.9984661249 1
< 0.1%
0.9981530692 1
< 0.1%
0.9980439595 1
< 0.1%
0.9979252775 1
< 0.1%
0.9977847805 1
< 0.1%
0.9977286328 1
< 0.1%
0.9976371499 1
< 0.1%
0.9973944638 1
< 0.1%

Interactions

2024-07-25T17:56:11.179902image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:55:59.994292image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:05.693797image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.329789image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.374665image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.282558image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.260010image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.295889image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:01.889109image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:05.946768image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.498767image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.496650image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.532528image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.379996image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.415875image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:02.675149image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:06.357720image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.675747image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.616635image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.642516image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.501982image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.529860image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:03.421063image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:06.623914image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.814729image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.740621image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.758069image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.634965image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.650878image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:03.760023image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:06.780851image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.943715image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.917600image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.877056image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.769952image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.768860image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:04.518935image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:06.953830image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.083697image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.034615image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.007041image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.903937image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.885193image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:05.059873image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:07.142811image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:08.226682image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:09.155574image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:10.131025image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-25T17:56:11.046919image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-07-25T17:56:16.805965image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
lbl 0lbl 1lbl 2lbl 255lbl 3mean_positiveweight
lbl 01.0000.5440.6000.8540.5760.907-0.133
lbl 10.5441.0000.7300.8360.5300.908-0.112
lbl 20.6000.7301.0000.7560.5520.861-0.069
lbl 2550.8540.8360.7561.0000.6650.9800.085
lbl 30.5760.5300.5520.6651.0000.7710.107
mean_positive0.9070.9080.8610.9800.7711.0000.059
weight-0.133-0.112-0.0690.0850.1070.0591.000

Missing values

2024-07-25T17:56:12.173150image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-25T17:56:12.371125image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

labelerweightlbl 0lbl 1lbl 2lbl 3lbl 255mean_positive
019668060.1471780.005471NaNNaNNaN0.0057540.005613
119817150.553252NaNNaNNaNNaN0.0016310.001631
221215420.2563820.012247NaNNaNNaN0.0129220.012584
321252410.394442NaNNaNNaNNaN0.0357770.035777
421266410.190362NaNNaNNaNNaN0.0073100.007310
521291430.1812560.004325NaNNaNNaN0.0045590.004442
615673540.215951NaNNaN0.000915NaN0.0009120.000914
721252270.212210NaNNaN0.003012NaN0.0029910.003001
821258430.183085NaNNaNNaNNaN0.1228610.122861
921261200.129929NaNNaN0.080777NaN0.0804410.080609
labelerweightlbl 0lbl 1lbl 2lbl 3lbl 255mean_positive
114591f45d620aef10b46a8660.054983NaNNaNNaNNaN0.9717310.971731
11460e7a663c716d256d7e9d20.119720NaNNaNNaNNaN0.9363290.936329
1146120947360.3735310.734449NaNNaNNaN0.3704960.552472
114626230f4781fb29640b9490.738379NaNNaNNaNNaN0.5086010.508601
1146320948390.514038NaNNaNNaNNaN0.8959530.895953
114648d04f7e9c254bcd3c56d0.408471NaNNaNNaNNaN0.8487180.848718
11465813f0a31d8067d2693df0.257199NaNNaNNaNNaN0.8682990.868299
11466c7278a50a5dfcfa6fc510.120579NaN0.941425NaNNaN0.8756520.908538
11467034b72cb0d2101353cfc0.235602NaN0.924658NaNNaN0.7013800.813019
114680a5e80cfe6d2313e2b3e0.073720NaN0.919079NaNNaN0.9323040.925692